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Jul 28, 2023
Merged

feature: add example links #258

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24 changes: 22 additions & 2 deletions packages/doc/docs/extensions/dbt.mdx
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Original file line number Diff line number Diff line change
Expand Up @@ -34,9 +34,25 @@ We need to install an additional package to integrate with dbt:

:::

## Using models in VulcanSQL
3. Setup `profiles.yaml`(if you are using DuckDB as the data source for your dbt project)

Using models of dbt is extremely easy, you only need to use the following syntax.
Add `persistent-path` to the `profiles.yaml` in the root of your VulcanSQL project like following

```yaml
- name: duckdb
type: duckdb
connection:
persistent-path: [duckdb db file path of your dbt project]
allow: "*"
```

## Setup of your dbt project

Please refer to the [dbt Quickstarts turotials](https://docs.getdbt.com/quickstarts)

## Using the dbt extension

Using models of dbt is extremely easy, you only need to use the following syntax in your VulcanSQL project.

```sql
{% dbt "model.<project-name>.<model-name>" %}
Expand All @@ -47,3 +63,7 @@ For example, to query all data from model `my_first_dbt_model` in the project `d
```sql
select * from {% dbt "model.demo.my_first_dbt_model" %}
```

## Examples

You can check out this [dbt-jaffle-shop](https://github.com/Canner/vulcan-sql-examples/tree/main/dbt-jaffle-shop) example for further details!
9 changes: 7 additions & 2 deletions packages/doc/docs/extensions/huggingface/huggingface-table-question-answering.mdx
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Expand Up @@ -2,7 +2,7 @@

The [Table Question Answering](https://huggingface.co/docs/api-inference/detailed_parameters#table-question-answering-task) is one of the Natural Language Processing tasks supported by Hugging Face.

Using the `huggingface_table_question_answering` filter.
## Using the `huggingface_table_question_answering` filter.

The result will be converted to a JSON string from `huggingface_table_question_answering`. You could decompress the JSON string and use the result by itself.

Expand Down Expand Up @@ -63,7 +63,7 @@ SELECT {{ products.value() | huggingface_table_question_answering(query=question
]
```

### Arguments
## Arguments

Please check [Table Question Answering](https://huggingface.co/docs/api-inference/detailed_parameters#table-question-answering-task) for further information.

Expand All @@ -73,3 +73,8 @@ Please check [Table Question Answering](https://huggingface.co/docs/api-inferenc
| model | N | google/tapas-base-finetuned-wtq | The model id of a pretrained model hosted inside a model repo on huggingface.co. See: https://huggingface.co/models?pipeline_tag=table-question-answering |
| use_cache | N | true | There is a cache layer on the inference API to speedup requests we have already seen |
| wait_for_model | N | false | If the model is not ready, wait for it instead of receiving 503. It limits the number of requests required to get your inference done |


## Examples

You can check out this [table-question-answering](https://github.com/Canner/vulcan-sql-examples/tree/main/huggingface/table-question-answering) example for further details!